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Econometrics encompasses the statistical methods which are especially important in modeling economic and financial phenomena. The study of economic and financial phenomena has three distinctions compared to other types of statistical problems.

1] Typically, the data sets are big, which is a result of several economic factors being followed for many days, hours, minutes, etc. This leads to particular emphasis on the large sample methods of statistics. For that reason, the method of maximum likelihood and its variations occupy a prominent spot.

2] Typically, the economic and financial phenomena are followed in time. Most often the moments of time are discretely spaced, corresponding to a particular time of day over many days, particular day of the year over many years, etc. Therefore, much emphasis is made on techniques designed for stochastic processes defined on a discrete time domain. These techniques are known as time series analysis.

3] Economic and financial data tend to exhibit strong heteroskedasticity (variation in the standard deviation over time) and autocorrelation. Much attention is devoted to developing the most efficient statistical techniques under these circumstances.

**ECONOMETRICS SUBCATEGORIES**

- Akaike Information Criterion
- ARIMA
- ARMA
- Bayesian Information Criterion
- Bayesian Statistics
- Bootstrap
- Brownian Motion
- Cross-validation
- Martingale
- Model Selection
- Multiple Linear Regression
- Stationary Process
- Stochastic Calculus
- Stochastic Process
- Stochastic Differential Equation
- Stochastic Volatility Modeling
- Statistical Software
- Time Series Analysis
- T-test
- White Noise

Greene, W. H. (2011). Econometric Analysis (7th ed). Upper Saddle River, NJ: Prentice Hall.

Lehmann, E.L., & Casella, G. (1998). Theory of Point Estimation (2nd ed). Springer.

Lehmann, E. L., & Romano, J. P. (2006). Testing Statistical Hypotheses (corrected 2nd printing of the 3rd ed). New York: Springer.

Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press.

Brockwell, P. J., & Davis, R. A. (1991). Time Series: Theory and Methods (2nd ed). New York: Springer.

Wei, W. W. S. (1990). Time Series Analysis: Univariate and Multivariate Methods. Redwood City, CA: Addison Wesley.

Tsay, R. S. (2005). Analysis of Financial Time Series. New Jersey: Wiley-Interscience.

Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1996). The Econometrics of Financial Markets (2nd ed). Princeton University Press.

Johnston, J., & DiNardo, J. (1997). Econometric Methods (4th ed). McGraw-Hill.

Wooldridge, J. M. (2013). Introductory Econometrics: A Modern Approach (5th ed). South-Western, Cengage Learning.

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